Open AccessSample Size Estimation and Power Analysis for Research Studies Using R
Author(s) -
Suma Ap,
K Suresh
Publication year - 2016
Publication title -
ira - international journal of applied sciences
Language(s) - English
Resource type - Journals
ISSN - 2455-4499
DOI - 10.21013/jas.v3.n2.p5
Subject(s) - sample size determination , statistics , sample (material) , mathematics , estimation , correlation , econometrics , engineering , physics , geometry , thermodynamics , systems engineering
Sample size estimation is very crucial in any research design. A research design with less sample size may give a biased result or inconclusive result. A research design with very large sample size than required results is waste of resources, time and energy. So, it is very essential to determine ‘ideal’ or ‘optimum’ sample size. This article gives formulae and R code for determining sample size for single mean, two means, single proportion, two proportions, proportion in survey type data, case control studies, cohort studies, correlation coefficient and difference between correlation coefficients.